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Optimization Model of an Efficient Collaborative Power Dispatching System for Carbon Emissions Trading in China

Author

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  • Qinliang Tan

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Research Center for Beijing Energy Development, Beijing 102206, China)

  • Yihong Ding

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yimei Zhang

    (Environmental Research Institute, Suzhou Research Institute, North China Electric Power University, Beijing 102206, China)

Abstract

In this paper, a collaborative power dispatching system (CPDS) was developed to maximize the profit of a regional biomass power system consisting of an independent power grid. A power generating, dispatching and carbon emissions trading system (CETS) could be engaged in joint strategic planning and operational execution. The principal of CPDS is interactive planning of generating units in power generation and carbon emissions trading. An efficient carbon emissions trading plan for a CPDS would lead to optimized power generation levels under available power production capacities and carbon emissions. In a case study, four generator policies are proposed by considering basic CETSs to comparatively analyze the function of each generator in the CPDS. Results of four scenarios are compared, showing that biomass energy could replace thermal units to a certain extent, the carbon emissions and coal consumption of the CPDS would lie at a lower level, and a pumped storage unit could adjust the load fluctuations. The results of a carbon trading analysis show that the CETS has no significant impact on the CPDS, but along with the increase in trading price or the decrease in the free quota, the economic interests of power plants will be reduced accordingly. This may lead to carrying out low-carbon projects and reducing carbon emissions. Therefore, it is imperative to reduce carbon emissions by replacing power units with high energy consumption, and improve the consumption capacity of renewable energy.

Suggested Citation

  • Qinliang Tan & Yihong Ding & Yimei Zhang, 2017. "Optimization Model of an Efficient Collaborative Power Dispatching System for Carbon Emissions Trading in China," Energies, MDPI, vol. 10(9), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:9:p:1405-:d:111899
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    Cited by:

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    2. Fangyi Li & Zhaoyang Ye & Xilin Xiao & Dawei Ma, 2019. "Environmental Benefits of Stock Evolution of Coal-Fired Power Generators in China," Sustainability, MDPI, vol. 11(19), pages 1-17, October.
    3. Zuoyu Liu & Weimin Zheng & Feng Qi & Lei Wang & Bo Zou & Fushuan Wen & You Xue, 2018. "Optimal Dispatch of a Virtual Power Plant Considering Demand Response and Carbon Trading," Energies, MDPI, vol. 11(6), pages 1-19, June.
    4. Jianzhong Zhou & Zhigao Zhao & Chu Zhang & Chaoshun Li & Yanhe Xu, 2017. "A Real-Time Accurate Model and Its Predictive Fuzzy PID Controller for Pumped Storage Unit via Error Compensation," Energies, MDPI, vol. 11(1), pages 1-24, December.
    5. Tan, Qinliang & Ding, Yihong & Ye, Qi & Mei, Shufan & Zhang, Yimei & Wei, Yongmei, 2019. "Optimization and evaluation of a dispatch model for an integrated wind-photovoltaic-thermal power system based on dynamic carbon emissions trading," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    6. Andrés Henao-Muñoz & Andrés Saavedra-Montes & Carlos Ramos-Paja, 2018. "Optimal Power Dispatch of Small-Scale Standalone Microgrid Located in Colombian Territory," Energies, MDPI, vol. 11(7), pages 1-20, July.
    7. Jing Liu & Yongping Li & Guohe Huang & Cai Suo & Shuo Yin, 2017. "An Interval Fuzzy-Stochastic Chance-Constrained Programming Based Energy-Water Nexus Model for Planning Electric Power Systems," Energies, MDPI, vol. 10(11), pages 1-23, November.

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